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Exploiting sink movement for energy-efficient load-balancing in wireless sensor networks
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International Symposium on Mobile Ad Hoc Networking & Computing archive
Proceeding of the 1st ACM international workshop on Foundations of wireless ad hoc and sensor networking and computing table of contents
Hong Kong, Hong Kong, China
SESSION: Routing and data collection table of contents
Pages 39-44  
Year of Publication: 2008
ISBN:978-1-60558-149-1
Authors
Gaotao Shi  Tianjin University, Tianjin, China
Minghong Liao  Harbin Institute of Technology, Haerbin, China
Maode Ma  Nanyang Technological University, Singapore, Singapore
Yantai Shu  Tianjin University, Tianjin, China
Sponsors
SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

Prolonging the lifetime is an important design consideration for battery powered wireless sensor networks. In a network with stationary sink, the sensor nodes located near the sink have to relay data from the rest of the network and thus deplete their energy very quickly. A sink mobility strategy was proposed in [1], which manages the sink to move along the periphery of the network for load-balancing. In this paper, based on the work in [1], we study the relationship of the energy efficiency and load-balancing. A novel mobility scheme for sink has been proposed to achieve the energy efficient load-balancing. By this scheme, the sink is controlled to move along a circle trajectory in a stationary for data buffering. All sensed data are forwarded into the annularity area firstly and then collected by the mobile sink. We find the optimum trajectory of sink movement with consideration of energy consumption and load-balancing and present how to find the location for the buffering area. Compared with the static sink scheme and the existing mobile sink scheme, the proposed is the most energy-efficient and it can reduce the load by 95% and 70%, respectively.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Gaotao Shi: colleagues
Minghong Liao: colleagues
Maode Ma: colleagues
Yantai Shu: colleagues